skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Food Service Building Asset Rating Methodology and Analysis

Journal Article · · ASHRAE Journal
OSTI ID:1459906
 [1];  [1];  [1];  [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Food Service buildings are extremely energy intensive, using about 5 to 7 times more energy per square foot than conventional commercial buildings. Energy intensive commercial kitchen appliances are the primary drivers, often necessitating high exhaust air requirements. Currently, no standardized method exists to directly compare energy efficiency between different Food Service buildings. Different restaurant types have various types of appliances and cooked food throughput requirements and thus it is challenging to make direct comparisons. Past attempts to categorize Food Service use types into “Quick-Service” and “Full-Service” led to the development of the Standard 90.1 prototype building models. However, these models do not address the highly diverse Food Service use types. This paper proposes a methodology to compare Food Service buildings through an asset rating system. By identifying all unique systems in a kitchen and creating a common baseline, this methodology identifies approaches for normalizing variations in kitchen requirements and to compare all Food Service buildings against one another.

Research Organization:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC05-76RL01830
OSTI ID:
1459906
Report Number(s):
PNNL-SA-132795
Journal Information:
ASHRAE Journal, Vol. 2018; ISSN 0001-2491
Publisher:
American Society of Heating, Refrigerating and Air-Conditioning EngineersCopyright Statement
Country of Publication:
United States
Language:
English

References (2)

Simulation-based coefficients for adjusting climate impact on energy consumption of commercial buildings journal November 2016
Development of building energy asset rating using stock modelling in the USA journal January 2016

Figures / Tables (7)